دانلود کتاب دستیار هوش مصنوعی خودتان را بسازید: راهنمای گام به گام برای سفارشی‌سازی GPT با OpenAI برای کاربران روزمره

We are living in a moment where AI is becoming accessible to everyone, not just engineers or researchers. Today, anyone with curiosity and willingness to experiment can design intelligent assistants that support real work, creativity, and everyday tasks. This book is written to guide you through that journey. My goal is to make complex ideas feel simple, practical, and grounded in real-world applications, so you can build custom GPTs with clarity and confidence. The chapters in this book follow a clear progression. We begin with the foundations, what GPTs are, how they work, and why customization matters. From there, you will build your first GPT, explore a structured approach to prompt engineering, and learn advanced techniques such as retrieval-augmented generation, chain-of-thought prompting, and few-shot learning. Finally, we turn to responsible AI practices, covering safety, grounding, and how to protect your GPTs from misuse. Whether you are just beginning your AI journey or looking to strengthen your technical skills, I hope this book becomes a resource you return to as both your ideas and the technology evolve. Let us discuss a brief overview of what each chapter covers. Chapter 1: Building with OpenAI GPTs – This chapter is an introduction to GPT fundamentals, the evolution of large language models, and why custom GPTs matter today. Chapter 2: GPT Use Cases and Examples – In this chapter, we will discuss the real-world applications of GPTs across industries and roles, helping you identify where AI can support your work and daily tasks. Chapter 3: Build Your First GPT in Minutes – This chapter is a guided, hands-on walkthrough where you create your first GPT, define its instructions, and learn the core building workflow. Chapter 4: Pentagram Framework for Effective Prompt Engineering – This chapters is a structured method developed to help you design highperforming GPTs. You will learn five essential components that shape clarity, consistency, and reliability. Chapter 5: Build RAG-Enhanced GPT for Customer Service – This chapter is a practical project introducing retrieval-augmented generation (RAG). You will build a customer service GPT grounded in real documents for accurate, context-aware responses. Chapter 6: Build a Chain-of-Thought Stock Insight GPT – In this chapter, you will learn how to guide GPT reasoning with chain-of-thought prompting. This chapter demonstrates how to generate structured analysis and explainable insights using stock data. Chapter 7: Few-Shot Learning for a Receipt Processing GPT – This chapter is a step-by-step build showing how to teach GPTs using examplebased learning. You will develop a receipt processing system that extracts structured data reliably. Chapter 8: GPT Actions and API Integration – In this chapter, you will discover how to connect your GPT to real-world tools and APIs. You will learn how to automate tasks, pull external data, and extend your GPT’s capabilities beyond the chat window. Chapter 9: Mitigating Prompt Injection and Jailbreak Attacks – This chapter is a practical guide to protecting your GPTs from malicious inputs and adversarial attempts. You will learn defensive strategies for maintaining safe behavior. Chapter 10: Grounding for Responsible AI – This chapter is an introduction to the five rings of responsible AI. This chapter shows how to build GPTs that are safe, transparent, well-grounded, and aligned with human values.